Chapter 7: Recent Trends in Technology

7.1 Concept of Artificial Intelligence (AI) and Robotics

Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems, enabling them to perform tasks such as learning, reasoning, problem-solving, perception, and decision-making without explicit human instructions.

Example: A self-driving car uses AI to analyze its surroundings, make decisions, and navigate roads safely.

Uses/Applications of AI:

1)      Natural Language Processing (NLP): Enables machines to understand, interpret, and generate human language. Example: Google Translate translates text between multiple languages.

2)      Computer Vision: Allows systems to analyze and interpret visual data like images and videos. Example: Apple's Face ID uses facial recognition to unlock devices securely.

3)      Recommendation Systems: Suggests personalized content, products, or services based on user preferences and behaviours. Example: YouTube recommends videos according to a user’s listening history.

4)      Predictive Analytics: Uses historical data and algorithms to predict future outcomes and trends. Example: Weather apps forecast conditions based on past and current data patterns.

5)      Robotics: AI-driven machines perform tasks autonomously or semi-autonomously. Example: Amazon’s warehouse robots automate sorting and inventory management.

6)      Healthcare Applications: Uses AI to improve patient care, diagnostics, and drug discovery. Example: AI-powered systems like PathAI assist in diagnosing diseases from pathology slides.

7)   Autonomous Vehicles   8)   Chatbots and Customer Service   9)   Intelligent Virtual Assistants

Positive Effects of AI:

a)       Improved healthcare and accurate diagnostics.

b)      Enhanced efficiency in industries and automation.

c)       Economic growth through innovation and new job creation.

d)      Better decision-making with data analysis.

Negative Effects of AI:

a)       Job displacement due to automation.

b)      Bias and discrimination in algorithms.

c)       Privacy concerns and data security issues.

d)      Increased dependence on technology.

Q1) Give five examples of AI applications in the education.

AI is revolutionizing education with innovative tools and applications that cater to diverse learning needs. Five Examples of AI application in the education are as follows:

1)      Personalized Learning: AI analyzes individual learning styles, strengths, and weaknesses to create tailored learning paths, enabling students to progress at their own pace.

2)      Intelligent Tutoring Systems: These systems offer personalized feedback and guidance, akin to having a dedicated tutor, adapting to students' pace and providing focused support.

3)      Automated Grading and Feedback: AI streamlines grading tasks for teachers, providing instant feedback to students on their work and highlighting areas for improvement.

4)      Predictive Analytics: AI predicts academic challenges and dropout risks by analyzing student data, helping educators intervene early and support student success.

5)      Accessibility Tools: AI enhances accessibility for students with disabilities, offering tools like real-time transcription, translation, and personalized learning materials.

Robotics:

Robotics is a branch of technology that involves the design, construction, operation, and use of robots to perform tasks autonomously or semi-autonomously. It integrates mechanical engineering, electronics, computer science, and artificial intelligence (AI) to develop machines that can mimic human actions or enhance efficiency in various domains.

Applications of Robotics

1. Manufacturing: Automated assembly lines, welding, painting, and quality control.
2. Healthcare: Robotic surgery, prosthetics, rehabilitation, and patient care.
3. Agriculture: Autonomous tractors, crop monitoring, precision farming.
4. Defence & Military: Drones, bomb disposal robots, surveillance systems.
5. Space Exploration: Mars rovers, robotic arms on spacecraft, satellite maintenance.
6. Automotive Industry: Self-driving cars, robotic assembly, automated inspections.
7. Logistics & Warehousing: Automated storage, order picking, delivery drones.
8. Service Industry: Robotic waiters, hotel assistants, cleaning robots.
9. Education & Research: AI-powered tutoring robots, research automation.
10. Entertainment & Gaming: Animatronics, virtual reality robots, robotic toys.

7.2 Concept of Cloud Computing

Cloud computing is the on-demand delivery of computing services, such as servers, storage, databases, networking, software, analytics, and intelligence, over the internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale. The main types of cloud computing are public, private, hybrid, and community clouds.

Example: Google Drive is a cloud-based storage service that allows users to store, access, and share files online from any device. 

Service Models of Cloud Computing:

Cloud computing offers various service models that provide users with different levels of control, flexibility, and responsibility. The three primary service models are:

1)      Infrastructure as a Service (IaaS): IaaS provides fundamental computing resources, such as servers, storage, and networking, over the internet (“the cloud”) to offer on-demand access to virtualized computing infrastructure. Examples:  Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

2)      Platform as a Service (PaaS): PaaS delivers a computing platform, such as operating systems, programming language execution environments, databases and web servers, over the internet (“the cloud”) to offer developers an environment for building, testing, and deploying applications. Examples:  Heroku, Google App Engine, and Microsoft Azure App Services.

3)      Software as a Service (SaaS): SaaS delivers applications over the internet (“the cloud”) to offer users access to software on demand, without the need for local installation or maintenance. Examples: Google Workspace, Microsoft 365, and Salesforce. 

Advantages and Disadvantages of Cloud Computing:

Advantages:

a)       Cost-effectiveness: Pay only for what you use, reducing upfront costs.

b)      Scalability: Easily adjust resources to meet changing demands.

c)       Flexibility: Access data and applications from anywhere with an internet connection.

d)      Reliability: High availability and disaster recovery features.

Disadvantages:

a)       Security risks: Data breaches and unauthorized access are potential threats.

b)      Internet dependency: Requires a stable internet connection.

c)       Vendor lock-in: Difficult to switch providers once you're committed.

      d)      Limited control: Reliance on third-party providers for infrastructure and maintenance. 

7.3 Concept of Big Data

Big Data is a term that describes extremely large and complex datasets that traditional data processing methods can't handle efficiently. It covers data that is characterized by high volume, high velocity, and high variety, often requiring advanced techniques and technologies to analyze and extract meaningful information. 

Characteristics of big data:

a)       Volume: Enormous amounts of data are generated every day from various sources.

b)      Velocity: Data is generated and processed rapidly, requiring real-time or near-real-time analysis.

c)       Variety: Data comes in diverse formats, including structured, unstructured, and semi-structured data.

d)      Veracity: The accuracy and reliability of data are crucial for meaningful analysis.

e)      Value: Extracting valuable insights from big data can drive informed decision-making and business growth.

Examples of Big Data:

a) Social media data (Facebook, Twitter, Instagram)

b) E-commerce transactions (Amazon, Flipkart)

c) Healthcare records (EHRs, MRI scans)

d) Banking and financial transactions

e) IoT sensor data (smart cities, wearables)

f) Search engine data (Google, Bing)

g) Streaming services data (Netflix, YouTube, Spotify)

h) Weather forecasting data (satellite and radar data)

Application Areas of Big Data:

1.       Healthcare: Predictive analytics, personalized treatments, hospital operations.

2.       Retail and E-Commerce: Recommendations, inventory management, market analysis.

3.       Banking and Finance: Fraud detection, credit risk assessment, algorithmic trading.

4.       Education: Student performance tracking, resource optimization, adaptive learning.

5.       Manufacturing: Predictive maintenance, process optimization, demand forecasting.

6.       Transportation and Logistics

7.       Media and Entertainment

8.       Government and Public Sector

9.       Agriculture

10.   Energy and Utilities

7.4 Concept of Virtual Reality (VR)

Virtual Reality (VR) is a technology that creates an immersive, computer-generated environment that simulates real-world or imaginary experiences. Users interact with this environment in a seemingly physical way, typically through specialized devices like VR headsets, gloves, or motion controllers.

Key Features of VR:

1.       Immersion: Provides a 360-degree view and realistic sensory feedback.

2.       Interaction: Allows users to interact with the virtual environment in real-time.

3.       Simulation: Recreates realistic scenarios or entirely imaginative worlds.

Components of VR:

Ø  Hardware: VR headsets (e.g., Oculus, HTC Vive), gloves, sensors, and controllers.

Ø  Software: Applications and simulations powered by VR engines like Unity or Unreal Engine.

Applications of VR:

1)       Gaming: Immersive gaming experiences.

2)       Education and Training: Simulating real-world scenarios for learning, like flight simulators.

3)       Healthcare: Therapy, rehabilitation, and surgical training.

4)       Entertainment: Virtual tours, movies, and concerts.

5)       Real Estate: Virtual property walkthroughs.

7.5 Concept of e-com, e-medicine, e-gov

Concept of E-Commerce (Electronic Commerce):

E-Commerce refers to the buying and selling of goods and services over the internet. It includes online marketplaces, retail platforms, and business-to-business (B2B) or business-to-consumer (B2C) transactions.

Ø  Examples: Amazon, eBay, Alibaba.

Ø  Key Features: Digital payments, product browsing, and customer reviews.

Advantages of E-Commerce:

1. Convenience: Shop anytime and anywhere with 24/7 accessibility.
2. Wide Reach: Access to a global customer base.
3. Lower Costs: Reduced expenses on physical stores and operations.
4. Personalized Shopping: Customized recommendations enhance user experience.

Disadvantages of E-Commerce:

1. Security Concerns: Risks of data breaches and online fraud.
2. Shipping Delays: Delivery times may not meet expectations.
3. Lack of Physical Interaction: Customers cannot inspect products before purchase.
4. Dependence on Technology: Requires reliable internet and systems.

Concept of E-Medicine (Electronic Medicine):

E-Medicine involves the use of digital technologies to deliver healthcare services remotely. It includes telemedicine, online consultations, and digital health records.

Ø  Examples: Telehealth apps like Practo, Teladoc Health.

Ø  Key Features: Virtual doctor-patient interactions, electronic prescriptions, and remote monitoring.

Concept of E-Government (Electronic Government):

E-Government refers to the use of technology, especially the internet, to provide government services, enhance public administration, and engage with citizens.

Ø  Examples: Online tax filing, digital voter registration, and e-governance portals.

Ø  Key Features: Transparency, accessibility, and efficiency in governance.

Advantages of E-Government (E-Gov):

1. Improved Accessibility: Citizens can access services anytime, from anywhere.
2. Efficiency: Streamlined processes reduce bureaucracy and delays.
3. Transparency: Easier access to government data promotes openness.

Disadvantages of E-Government (E-Gov):

1. Digital Divide: Limited access for those without internet or digital skills.
2. Security Risks: Vulnerability to data breaches and cyber-attacks.
3. Privacy Concerns: Risks related to the collection and storage of sensitive personal data.

Challenges of Implementing E-Governance in Developing Countries:

1. Lack of Infrastructure: Limited access to reliable internet and technology in rural areas.
2. Low Digital Literacy: Citizens and government employees may lack the skills to use digital platforms.
3. High Costs: Initial investment in technology and maintenance is often unaffordable.
4. Cybersecurity Risks: Vulnerability to cyber-attacks and concerns over data privacy.
5. Resistance to Change: Resistance from citizens and officials accustomed to traditional systems.
6. Digital Divide: Unequal access to e-Government services between urban and rural areas.

7.6 Concept of Mobile Computing

Mobile Computing refers to the ability to use computing devices (such as smartphones, tablets, and laptops) to access, process, and share data while on the move. It enables users to perform tasks, access information, and communicate wirelessly, without being tied to a fixed location.

Key Components of Mobile Computing:

1.       Mobile Hardware: Devices like smartphones, laptops, and tablets.

2.       Wireless Networks: Cellular networks (3G, 4G, 5G), Wi-Fi, Bluetooth, etc., enable connectivity.

3.       Mobile Software: Operating systems (iOS, Android) and applications designed for mobile devices.

4.       Cloud Computing: Storing and accessing data and services over the internet, enabling mobility.

Applications of Mobile Computing:

1.       Communication: Instant messaging, video calls, and social media.

2.       Navigation: GPS-based applications like Google Maps.

3.       E-commerce: Online shopping and banking apps.

4.       Work Productivity: Email, document editing, and collaboration tools on mobile devices.

7.7 Concept of IoT (Internet of Things):

The Internet of Things (IoT) refers to the network of physical devices, vehicles, appliances, and other physical objects that are embedded with sensors, software, and network connectivity, allowing them to collect and share data. These devices, often referred to as "smart objects," can range from simple everyday items like smart thermostats to complex industrial machinery.   

In simpler terms, it's about connecting everyday objects to the internet, allowing them to collect and share data.  

Key Features of IoT are as follows:

a) Connectivity: Devices are connected to the internet or other networks.

b) Sensors: Devices collect data from their environment.

c) Data Exchange: Devices share data with each other and with central systems.

d) Automation: Often these systems are used to automate processes.

Applications of IoT are as follows:

a) Smart Homes (e.g. smart thermostats, security cameras)

b) Healthcare (e.g. wearable health monitors)

c) Industrial IoT (IIoT) (e.g. predictive maintenance in factories)

d) Agriculture (e.g. smart irrigation systems)

e) Smart Cities (e.g. traffic management, waste monitoring)

Out of Syllabus but important according to old syllabus:

Social media:

Social media refers to interactive computer-mediated technologies that facilitate the creation and sharing of information, ideas, interests, and other forms of expression via virtual communities and networks.

Positive Impacts of Social Media:

• Enhanced Communication: Connects people across distances, fostering relationships and facilitating communication.   
• Information Dissemination: Rapidly spreads news, information, and ideas, raising awareness about important issues.   
• Community Building: Creates online communities around shared interests, providing support and a sense of belonging.   
• Business Growth: Enables businesses to reach wider audiences, build brand awareness, and connect with customers.   
• Social and Political Activism: Facilitates social movements and political mobilization.   
• Creative Expression: Provides a platform for individuals to share their creativity and connect with others who share similar interests.   

Negative Impacts of Social Media:

• Mental Health Concerns: Can contribute to anxiety, depression, low self-esteem, and feelings of inadequacy due to social comparison and cyberbullying.   
• Misinformation and Echo Chambers: Spreads misinformation and reinforces existing biases, limiting exposure to diverse perspectives.   
• Privacy Concerns: Raises concerns about data privacy and the potential for misuse of personal information.   
• Addiction: Can be addictive, leading to excessive use and neglecting real-life interactions and responsibilities.   
• Cyberbullying and Harassment: Facilitates cyberbullying, harassment, and online abuse.   
• Social Comparison: Can lead to unrealistic expectations and a distorted perception of reality.

E-Learning: 

E-Learning refers to the use of electronic media, such as the internet, computers, and digital platforms, to deliver educational content and facilitate learning. It enables students to access courses, training, and resources remotely, without the need for traditional classroom settings.

Types of E-Learning:

1.       Synchronous: Real-time classes with instructors and students interacting (e.g., live webinars).

2.       Asynchronous: Pre-recorded lessons and materials that learners can access at any time (e.g., MOOCs, video tutorials).

3.       Blended Learning: Combines online learning with traditional face-to-face education. 

Advantages of E-Learning:

a)      Flexibility to learn anytime, anywhere. Example: A working professional can take online courses whenever it fits her schedule, whether day or night.

b)      Cost-effective, as it reduces the need for physical infrastructure. Example: A company saves money by offering online employee training instead of organizing physical classes with travel and room costs.

c)       Access to a wide variety of resources and expert instructors. Example: A person can take an online graphic design course with top instructors from Skillshare, using video tutorials and project files. 

Challenges of E-Learning:

·         Limited personal interaction and networking opportunities.

·         Technical issues and the digital divide (lack of access to technology).

·         Self-discipline required to stay motivated and complete courses.

Chapter 6: Software Process Model (SPM)

2081 GIE Set A Q.No. 13 How does the System Development Life Cycle (SDLC) facilitate the efficient planning and execution of software development projects?

Ans:

The System Development Life Cycle (SDLC) facilitates efficient planning and execution of software development projects by providing a structured, step-by-step approach to software creation. It ensures that projects are completed on time, within budget, and with high quality. Here’s how SDLC helps:

1.       Structured Approach for Development: It divides development into phases (planning, design, implementation, testing, deployment, and maintenance), reducing complexity and ensuring systematic progress.

2.       Better Planning and Resource Management: It helps in better resource management, avoiding delays and cost overruns by clearly defining requirements, budget, and timelines

3.       Improved Quality and Risk Management: It improves software quality through rigorous testing, early error detection, and risk mitigation.

4.       Clear Roles and Responsibilities: It assigns clear roles and responsibilities, enhancing team collaboration and communication.

5.       Flexibility with Different Models: SDLC supports different methodologies like Waterfall, Agile, Spiral, allowing teams to choose the best approach based on project needs.

 

2081 GIE Set B Q.No. 13 Explain the importance of the system analysis phase of SDLC.

Ans:

The System Analysis phase of the Software Development Life Cycle (SDLC) is crucial because it lays the foundation for a successful project by identifying business needs, defining requirements, and ensuring feasibility. Below are the key reasons why system analysis is important:

1.       Understanding Requirements: Gathers and defines functional and non-functional requirements to ensure stakeholder expectations are clearly documented and aligned.

2.       Feasibility Study: Evaluates technical, economic, and operational feasibility to help decision-makers determine if the project should proceed.

3.       Identifying Problems and Solutions: Analyses the current system to identify inefficiencies and design solutions that effectively address user needs.

4.       Defining System Scope: Clearly outlines the system's boundaries to prevent scope creep and avoid delays or cost overruns.

5.       Reducing Risks: Identifies potential risks early and ensures compliance with legal, security, and performance standards.

6.       Facilitating Better System Design: Provides a clear roadmap for the design phase, enabling developers to build an efficient and scalable system.

 

2079 GIE Set A Q.No.13 Explain the importance of the system testing of the system development life cycle (SDLC).

Ans:

The System Testing phase of the Software Development Life Cycle (SDLC) is crucial because it ensures that the developed software meets the specified requirements and functions correctly before deployment. Below are the key reasons why system testing is important:

1. Ensures Functional Accuracy: Verifies that all system components work as intended and meet business and user requirements.

2. Detects Bugs and Errors Early: Identifies defects before deployment, reducing the cost of fixing errors compared to later stages.

3. Validates System Performance: Tests speed, stability, and scalability under various conditions to ensure the system handles expected workloads.

4. Ensures Security and Data Integrity: Checks for vulnerabilities to prevent security breaches and ensures sensitive data is protected.

5. Confirms Compatibility: Ensures the system works across devices, operating systems, browsers, and integrates with third-party applications.

6. Enhances User Satisfaction: Identifies usability issues to ensure smooth navigation, readability, and accessibility for a better user experience.

7. Compliance with Industry Standards: Ensures the software meets legal, regulatory, and industry standards, helping obtain necessary certifications.

 

2081 Q.No.13 How do various requirement gathering techniques help in achieving a careful grasp of user needs and requirements during SDLC’s analysis phase?  [5]

Ans:

Various requirement-gathering techniques help achieve a careful grasp of user needs and requirements during the analysis phase of the Software Development Life Cycle (SDLC) in the following ways:

1.       Comprehensive Understanding – Techniques like interviews and workshops enable direct interaction with stakeholders, helping to clarify business needs, expectations, and constraints.

2.       Diverse Perspectives – Methods like surveys, questionnaires, and brainstorming ensure that inputs from a broad range of users are collected, leading to a well-rounded understanding of requirements.

3.       Real-World Insights – Observation and document analysis provide practical insights into existing workflows, uncovering implicit needs that users may not explicitly mention.

4.       Validation and Refinement – Prototyping and use cases/user stories allow users to visualize and interact with early models, ensuring that the gathered requirements are accurate, feasible, and aligned with expectations.

5.       Efficiency and Accuracy – A combination of these techniques reduces the risk of missing critical requirements, prevents misunderstandings, and ensures that the final software solution effectively addresses user needs.

 

2080 GIE Set A Q.No.13 Describe the different requirement gathering methods for the development of software.  [5]

Ans:

Requirement collection is a critical phase in the Software Development Life Cycle (SDLC) as it lays the foundation for the entire project. Here are some effective methods for collecting requirements:

1. Interviews: Conduct one-on-one or group interviews with stakeholders, end-users, and clients to gather detailed information and understand their needs and expectations.

2. Surveys and Questionnaires: Distribute structured surveys or questionnaires to a larger audience to gather information.

3. Workshops: Organize collaborative workshops with stakeholders to discuss and prioritize requirements.

4. Observation: Observe users in their natural work environment to understand their workflows and identify potential improvements.

5. Prototyping: Develop prototypes or mock-ups of the proposed system to gather feedback from users.

6. Document Analysis: Review existing documentation such as manuals, system specifications, and reports to extract relevant information.

7. Use Cases and User Stories: Create detailed use cases or user stories to describe how users will interact with the system.

8. Brainstorming: Conduct brainstorming sessions to generate ideas and requirements with a group of stakeholders.

 

2080 GIE Set B Q.No.13 Explain the agile software development methodology in brief.   [5]

Ans:

The Agile Software Development Model is an iterative and incremental approach to software development which emphasizes flexibility, collaboration, and customer satisfaction through continuous delivery of valuable, working software. Agile is particularly effective in dynamic and fast-changing environments where requirements evolve over time.

Core Principles of Agile (as per the Agile Manifesto) are as follows:

1. Customer Collaboration: Engage with customers regularly to ensure their needs are being met.

2. Working Software: Deliver functional software frequently, typically in short iterations.

3. Individuals and Interactions: Prioritize teamwork and communication over rigid processes and tools.

4. Responding to Change: Adapt to changes in requirements, even late in the development process.

Advantages of Agile:

1. Customer Collaboration: Frequent feedback ensures the final product meets user expectations.
2. Flexibility: Easily accommodates changes in requirements throughout development.
3. Early and Continuous Delivery: Delivers value to the customer early and regularly.

Disadvantages of Agile:

1. Scope Creep: Changes can lead to scope creep if not managed properly.
2. Documentation: May result in inadequate documentation.
3. Resource Intensive: Requires significant time and effort from team members and stakeholders.

 

2079 GIE Set B Q.No.13 Explain requirement analysis phase of SDLC.  [5]

Ans:

The Requirement Analysis phase in the Software Development Life Cycle (SDLC) is a crucial stage where the primary goal is to gather, analyse, and document the requirements for the software being developed. Here's a breakdown of this phase:

1)      Identify Stakeholders: Determine all individuals or groups involved in or affected by the software system.

2)      Gather Requirements: Collect detailed functional and non-functional requirements from stakeholders using various techniques.

3)      Document Requirements: Record the gathered requirements in a structured format, usually in a Software Requirements Specification (SRS) document.

4)      Analyse and Prioritize Requirements: Evaluate requirements for feasibility, resolve conflicts, and prioritize them based on importance.

5)      Define System Specifications: Establish clear system specifications, including technical, security, and compliance needs, to guide development.

In conclusion, the Requirement Analysis phase ensures that the development team understands what needs to be built, aligning the software with the business objectives and user needs, laying a solid foundation for the rest of the SDLC.

 

2078 Set B Q.No.13 Describe the waterfall software development model with pros and cons.  [5]

2074 Set A Q. No. 6 Describe the waterfall model to explain the SDLC.  [5]

2073 Set C Q. No. 6 What are the major activities in SDLC with based on waterfall model? [5]

Ans:

The Waterfall Model is a linear and sequential approach to software development, where each phase of the development process 1 must be completed before moving on to the next 2 one. It's like a waterfall, where the water flows steadily downwards through different stages.  

Phases of the Waterfall Model:

1. Requirements Gathering and Analysis: The project's goals, scope, and requirements are defined.

2. Design: The system's architecture, components, and interfaces are designed.

3. Implementation (Coding): The software is developed based on the design.

4. Testing: The software is rigorously tested to identify and fix bugs.

5. Deployment: The software is released to the end-users.

6. Maintenance: Ongoing support and maintenance of the software.

Advantages (Pros):

a) Simple and easy to understand.

b) Provides a structured approach to development.

c) Well-suited for projects with well-defined requirements.

Disadvantages (Cons):

a) Inflexible: Difficult to accommodate changes once development begins.

b) Time-consuming: Delays in one phase can significantly impact the project timeline.

c) Limited customer involvement: Customer feedback is primarily seen at the end of the project.

 

2079 Set A Q.No.8 What are the major activities performed to design the software? Describe briefly.  [5]

Ans:

The major activities performed in software design are as follows:

1.       Requirement Analysis: Understanding and gathering user needs, business goals, and system requirements to define the scope of the software.

2.       System Architecture Design: Defining the overall system structure, including components, modules, data flow, and interactions between different parts of the software.

3.       User Interface (UI) Design: Creating the layout, navigation, and visual elements to ensure an intuitive and user-friendly experience.

4.       Database Design: Structuring data storage, defining tables, relationships, and ensuring efficient data retrieval and management.

5.       Module and Component Design: Breaking the system into smaller, manageable modules with clear functions and responsibilities.

6.       Algorithm and Logic Design: Developing logical workflows, algorithms, and processing methods for efficient execution of software tasks.

7.       Prototyping and Review: Creating prototypes or mockups to visualize functionality, gather feedback, and refine the design before implementation.

 

 

2078 Set C Q.No.6 What is feasibility study? Explain.  [5]

2072 Set E Q. No. 6 2070 Set C Q. No. 6 2068 Q. No. 5 2067 Q. No. 5 2064 Q. No. 9 2062 Q. No. 5 What is feasibility study? Explain different levels of feasibility study.  [2+3]

2071 Supp Q. No. 6 What is feasibility study? Why is it necessary before designing a system?  [2+3=5]

2076 Q. No. 6 Define SDLC. Describe the feasibility analysis methods.  [2+3]

2071 Set D Q. No. 6 Describe different levels of feasibility study.  [5]

2072 Set D Q. No. 6 Describe the components of feasibility study. [5]

Ans:

A feasibility study is a detailed analysis that assesses the practicality and viability of a proposed project or plan. It aims to determine whether the project is likely to succeed by evaluating various factors (level/types/components) as follows:   

1. Technical Feasibility: Assesses the availability and suitability of the required technology and resources.  

2. Economic Feasibility: Evaluates the financial viability of the project, including cost-benefit analysis, return on investment, and funding options.  

3. Legal Feasibility: Examines potential legal and regulatory implications, such as intellectual property rights, data privacy, and licensing requirements.  

4. Operational Feasibility: Assesses the impact of the project on existing operations, including organizational changes, user acceptance, and training needs.

5. Scheduling Feasibility: Determines the project timeline, resource allocation, and potential risks and develops contingency plans.

Some benefits of a Feasibility Study are as follows:

1. Informed Decision-Making: Helps make informed decisions about project viability.

2. Risk Mitigation: Identifies and addresses potential risks early on.

3. Resource Allocation: Optimizes resource allocation and budgeting.

4. Improved Project Planning: Provides a solid foundation for project planning.

5. Enhanced Stakeholder Buy-in: Builds confidence and support for the project.

 

2078 Set B Q.No.7 Describe the desirable characteristics of a system analyst.  [5]

2072 Set D Q. No. 7 Who is system analyst? List out characteristics of system analyst. [1+4]

Ans:

A System Analyst is a professional who analyses and designs information systems to meet the needs of an organization, acting as a bridge between stakeholders and the technical development team.

The desirable characteristics of a system analyst are as follows:

1. Analytical Skills: The ability to analyse complex systems, identify inefficiencies, and translate business requirements into technical solutions.

2. Communication Skills: Strong verbal and written communication to interact with stakeholders and convey technical details effectively.

3. Documentation Skills: The capability to create clear and detailed documentation for system requirements, workflows, and project reports.

4. Problem-Solving Skills: The skill to identify issues in systems and develop efficient, scalable, and secure solutions.

5. Collaboration Skills: The ability to work with diverse teams, coordinate efforts, and align stakeholders with project objectives.

In conclusion, a system analyst must possess a combination of analytical, communication, documentation, problem-solving, and collaboration skills to effectively analyse, design, and implement efficient systems.

 

2076 Set A Q.No.8 What are roles of system analyst in SDLC phase?  [5]

2075 Set B Q. No. 7 Describe the major role and responsibility of system analyst in SDLC phase. [5]

2075 Set A Q. No. 6 2073 Set D Q. No. 6 2065 Q. No. 5 Who is system analyst? Explain the role of system analyst. [1+4]

Ans:

A System Analyst is a professional who analyses and designs information systems to meet the needs of an organization, acting as a bridge between stakeholders and the technical development team.

Role and responsibilities of a System Analyst in SDLC phases are as follows:

1. Requirement Gathering and Analysis: Gather, analyse, and document stakeholder requirements.

2. Feasibility Study: Evaluate technical, economic, and operational feasibility.

3. System Design: Create detailed design documents, including architecture and data models.

4. Communication and Coordination: Act as a liaison between stakeholders and the development team.

5. Documentation: Prepare comprehensive documentation, including requirements and user manuals.

6. Validation and Verification: Ensure the system meets specified requirements and functions as intended.

7. Support and Maintenance: Provide ongoing support and maintenance after deployment.

8. Change Management: Manage changes in requirements and scope during the project.

 

2076 GIE Set B Q.No.6 What are the importances of SDLC in software development process?   [5]

2073 Set D Q. No. 7 Write the importance and necessity of SDLC.   [5]

2072 Set E Q. No. 13 Write the importance of SDLC.  [5]

Ans:

The Software Development Life Cycle (SDLC) is a structured approach used by software development teams to design, develop, test, and deploy high-quality software. It's a framework that ensures a systematic and efficient process, minimizing risks and maximizing the chances of a successful project.

The importances of SDLC in software development process and necessity come from the following key benefits:

1) Structured Approach: SDLC provides a systematic and organized approach to software   development, breaking down the process into distinct phases.

2) Enhanced Quality: By following SDLC, teams can ensure high-quality software through rigorous testing and continuous improvement.

3) Efficient Resource Utilization: SDLC helps optimize resource allocation, reduce costs, and increase productivity.

4) Improved Communication and Collaboration: SDLC fosters effective communication and collaboration among team members, leading to better teamwork and project outcomes.

5) Adaptability to Change: SDLC models like Agile allow for flexibility and adaptability to changing requirements, ensuring that the software meets evolving needs.

In conclusion, SDLC is a critical tool for software development organizations. By following to its principles, teams can deliver high-quality software on time and within budget, ensuring customer satisfaction and business success.

 

2070 Supp Q. No. 6 Explain SDLC with appropriate diagram.  [5]

2072 Set C Q. No. 6 Describe SDLC with diagram.  [5]

2073 Supp Q. No. 6 Explain the system development phase. [5]

Ans:

The Software Development Life Cycle (SDLC) is a structured approach used by software development teams to design, develop, test, and deploy high-quality software.

SDLC involves a series of phases (Stages/Steps), each with specific goals and activities as follows:

1.       Planning: The goal of this phase is to Define the project scope, identify requirements, and create a solid project plan.

2.       Analysis: The goal of this phase is to Thoroughly understand the user requirements and system needs.

3.       Design: The goal of this phase is to Create a blueprint for the software, outlining its architecture, components, and user interface.

4.       Development (Implementation): The goal of this phase is to Translate the design into actual code.

5.       Testing: The goal of this phase is to Identify and fix bugs to ensure software quality.

6.       Deployment: The goal of this phase is to Release the software to the production environment.

7.       Maintenance: The goal of this phase is to Keep the software up-to-date and functioning optimally.

 

2075 GIE Q. No. 6 Explain system analysis phase of SDLC. [5]

2074 Supp Q. No. 6 List the steps of SDLC. Explain System Analysis Phase. [2+3]

2071 Set C Q. No. 6 What is system analysis and design? Describe briefly. [5]

2075 Set B Q. No. 6 List out different stages of system development life cycle and explain any two stages of them. [1+2+2]

2074 Set B Q. No. 6 What are the software development process phases in SDLC? Explain any one phase. [2+3]

Ans:

The Software Development Life Cycle (SDLC) is a structured approach used by software development teams to design, develop, test, and deploy high-quality software. The steps of SDLC (Software Development Life Cycle) are:

1.       Planning

2.       System Analysis

3.       System Design

4.       Implementation (Coding)

5.       Testing

6.       Deployment

7.       Maintenance

2. System Analysis Phase:

The System Analysis phase is crucial as it determines what the system needs to do to meet business objectives. It involves:

Ø  Requirement Gathering – Understanding user needs and expectations.

Ø  Feasibility Study – Checking if the project is technically, financially, and operationally feasible.

Ø  System Modelling – Creating diagrams like Data Flow Diagrams (DFDs) and Entity-Relationship Diagrams (ERDs) to visualize system processes.

Ø  Problem Identification – Analysing current system inefficiencies and suggesting improvements.

Ø  Documentation – Recording the findings and system requirements for future reference.

This phase ensures that developers and stakeholders have a clear understanding of what needs to be built before moving to design and implementation.

 

3. System Design Phase:

The System Design phase of SDLC focuses on defining the architecture, components, and user interface of the system based on the requirements gathered in the System Analysis phase. It acts as a blueprint for the development process.

Key Aspects of System Design are as follows:

1.       High-Level Design (HLD) – Defines the overall system architecture, including modules, databases, interfaces, and data flow.

2.       Low-Level Design (LLD) – Provides detailed designs for each module, including algorithms, database structures, and function specifications.

3.       Database Design – Specifies how data will be stored, organized, and accessed.

4.       User Interface (UI) Design – Creates wireframes and layouts for user interaction.

5.       Security and Performance Considerations – Defines authentication, encryption, and system efficiency requirements.

6.       Design Documentation – Records all design decisions for developers and stakeholders.

This phase ensures that the system is well-structured, scalable, and meets business requirements before moving to the Implementation (Coding) phase.

 

2075 GIE Q. No. 7 2075 Set A Q. No. 7 2073 Supp Q. No. 7 Define the terms DFD and E-R diagram. [2.5+2.5]

Ans:

1.       Data Flow Diagram (DFD)

Purpose: Models how data moves through the system and how it's processed. Focuses on the flow of data between processes, data stores, and external entities.

Focus: Shows internal processes, data storage, and interactions with external entities.

Key Components:

o   Processes: Actions that transform incoming data (represented by circles or rounded rectangles).

o   Data Flow: Arrows showing the direction of data.

o   Data Stores: Places where data is stored (represented by open rectangles).

o   External Entities: Sources or destinations of data (e.g., users or other systems).

Level of Detail: Can be broken down into multiple levels (e.g., Level 0, Level 1) for greater detail.

Usage:

o   To visualize data movement and processing.

o   To understand how different parts of the system interact with data.

2.       Entity-Relationship Diagram (ERD)

Purpose: Describes the data structure and the relationships between entities in a database. Focuses on how data is organized and related in a system.

Focus: Represents entities (objects or concepts) and the relationships between them, mainly for database design.

Key Components:

o   Entities: Represent objects or concepts (e.g., "Customer", "Order").

o   Attributes: Properties of entities (e.g., "Customer Name", "Order Date").

o   Relationships: How entities are related (e.g., "Customer places Order").

o   Primary Keys: Unique identifiers for each entity instance.

Level of Detail: Provides a detailed representation of how data is structured within a system (more focused on database design).

Usage:

o   To design and organize databases.

o   To identify relationships and ensure data integrity.

 

2075 Set B Q. No. 6 What is E-R diagram? Write the meaning of graphical symbols used in E-R diagram. [5]

Ans:

An E-R (Entity-Relationship) Diagram is a graphical representation of entities, their attributes, and the relationships between them in a database. It is widely used in database design to visualize the structure of a system before implementing it.

The meaning of graphical symbols used in E-R diagram are as follows in tabular form: